• The Journal of Engineering Geology
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• v.23 no.4
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• pp.467-476
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• 2013

With increasing interest in environmental issues and the quality of surface water becoming inadequate for water supply, the Korean government has launched a groundwater development policy to satisfy the demand for clean water. To drive this policy effectively, it is essential to guarantee the accuracy of sustainable groundwater yield and groundwater use amount. In this study, groundwater use was monitored over several years at various locations in Korea (32 cities/counties in 5 provinces) to obtain accurate groundwater use data. Statistical analysis of the results was performed as a method for estimating rational groundwater use. For the case of groundwater use for living purposes, we classified the cities/counties into three regional types (urban, rural, and urban-rural complex) and divided the groundwater facilities into five types (domestic use, apartment housing, small-scale water supply, schools, and businesses) according to use. For the case of agricultural use, we defined three regional types based on rainfall intensity (average rainfall, below-average rainfall, and above-average rainfall) and the facilities into six types (rice farming, dry-field farming, floriculture, livestock-cows, livestock-pigs, and livestock-chickens). Finally, we developed groundwater-use estimation equations for each region and use type, using cluster analysis and regression model analysis of the monitoring data. The results will enhance the reliability of national groundwater statistics.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.936-946
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• 2009

A graph cuts method has recently attracted a lot of attentions for image segmentation, as it can globally minimize energy functions composed of data term that reflects how each pixel fits into prior information for each class and smoothness term that penalizes discontinuities between neighboring pixels. In previous approaches to graph cuts-based automatic image segmentation, GMM(Gaussian mixture models) is generally used, and means and covariance matrixes calculated by EM algorithm were used as prior information for each cluster. However, it is practicable only for clusters with a hyper-spherical or hyper-ellipsoidal shape, as the cluster was represented based on the covariance matrix centered on the mean. For arbitrary-shaped clusters, this paper proposes graph cuts-based image segmentation using mean shift analysis. As a prior information to estimate the data term, we use the set of mean trajectories toward each mode from initial means randomly selected in $L^*u^*{\upsilon}^*$ color space. Since the mean shift procedure requires many computational times, we transform features in continuous feature space into 3D discrete grid, and use 3D kernel based on the first moment in the grid, which are needed to move the means to modes. In the experiments, we investigate the problems of mean shift-based and normalized cuts-based image segmentation methods that are recently popular methods, and the proposed method showed better performance than previous two methods and graph cuts-based automatic image segmentation using GMM on Berkeley segmentation dataset.

• Ocean and Polar Research
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• v.26 no.2
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• pp.199-205
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• 2004

$SiO_2$ and CaO are added to decrease the smelting temperature in the reduction-smelting method for manganese nodule processing. These elements are components of the manganese nodules and might be very important controlling factors in the processing due to the locally variable content. The 707 chemical data of manganese nodules acquired from 1994 to 2001 in KODOS(Korea Deep Ocean Survey) area were used for the hierarchical cluster analysis. The chemical data were classified by the morphological types, and the averages of the chemical data for each station were classified by the facies groups and the localities. All data are plotted on the $SiO_2-CaO-MnO$ phase diagram at $1773^{\circ}K$ to compare with the best compositional area in the nodule smelting. Variations and distributions of $SiO_2$ and CaO in KODOS nodules were also reviewed. The mineral phases assigned by the cluster analysis are CFA(Carbonate Fluorapatite), Fe-oxide, Al-silicate, and Mn-oxide. MnO contents are generally higher than $SiO_2$ contents in most of the morphological types except for the Is- and It-type. The Dt- and Tt-type show wider range and the E-types show high anomaly in their CaO contents. The stations which belong to facies group A and B show generally higher MnO contents than $SiO_2$ contents, however, the stations of facies group C and D show wide range in their MnO and $SiO_2$ contents. It seems to be very important to control the $SiO_2$ contents in the processing because of the wide range in the northern area. The additions of approximately 10 wt.% CaO and 10 wt.% $SiO_2$ are recommended for the northern area, whereas, the additions of approximately 10 wt.% CaO and 20 wt.% $SiO_2$ are recommended for the southern area.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.41-53
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• 2015

In meteorological field, many researchers have tried to develop micro scale weather analysis modules for providing real-time weather information service in the metropolitan area. This effort enables us to cope with various economic and social harms coming from serious change in the micro meteorology of a metropolitan area due to rapid urbanization such as quantitative expansions in its urban activity, growth of population, and building concentration. The accuracy of the micro scale weather analysis modules (MSWAM) directly related to usefulness and quality of the real-time weather information service in the metropolitan area. This paper design a evaluation system along with verification tools that sufficiently accommodate spatio-temporal characteristics of the outputs of the MSWAM. For this we proposes a test for the equality of mean vectors of the output series of the MSWAM and corresponding observed time series by using a spectral analysis technique. As a byproduct, a time series cluster analysis method, using a function of the test statistic as the distance measure, is developed. A real data application is given to demonstrate the utility of the method.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.213-230
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• 2020

Until now, various educational budgets, facilities, and programs have been put into school education, but the results have not been clearly evaluated. This study presents a model to analyze the effectiveness of educational support for students in high schools across the country. In this model, we first use EM cluster analysis to make clusters with similar inputs for school operation, and then calculate the relative efficiency in each cluster by using Network DEA analysis. The Network DEA analysis has a two-stage structure where the first stage uses six inputs in terms of school infrastructure to generate outputs such as the number of academic persistence. In the Network DEA analysis, the second stage uses 10 inputs in terms of school programs to generate outputs such as the number of enrollees to higher learning and the number of employees and per capita usage of library as the connection variable. Based on the efficiency analysis results, Tier analysis is performed by applying the Euclidean distance to select targets for benchmarking. In this study, we applied the model to analyze the efficiency of educational support by collecting data regarding student education support in general and vocational high school nationwide. The stepwise benchmarking method proposed that the target be selected for efficiency improvement step by step, taking into account inefficient school elements to complement the problem of the choice of benchmarking targets. Based on this study, it is expected that schools with low efficiency of educational support for students will be used as basic data for stepwise benchmarking for efficient operation of educational support for students.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.14-28
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• 2010

The aim of this study is to investigate crime hotspot areas using the spatio-temporal cluster analysis which is possible to search simultaneously time range as well as space range as an alternative method of existing hotspot analysis only identifying crime occurrence distribution patterns in urban area. As for research method, first, crime data were collected from criminal registers provided by official police authority in M city, Gyeongnam and crime occurrence patterns were drafted on a map by using Geographic Information Systems(GIS). Second, by utilizing Ripley K-function and Space-Time Scan Statistics analysis, the spatio-temporal distribution of crime was examined. The results showed that the risk of crime was significantly clustered at relatively few places and the spatio-temporal clustered areas of crime were different from those predicted by existing spatial hotspot analysis such as kernel density analysis and k-means clustering analysis. Finally, it is expected that the results of this study can be not only utilized as a valuable reference data for establishing urban planning and crime prevention through environmental design(CPTED), but also made available for the allocation of police resources and the improvement of public security services.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.26 no.3
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• pp.350-366
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• 2016

Objectives: No 3D anthropometric analyses have been conducted for Korean children's faces for the purpose of designing respiratory protective devices. The aim of this study was to develop masks against yellow dust and fine particulates, particularly for children in Korea. Methods: This study utilized a 3D scanning method to obtain 16 facial anthropometric data from children, ages of 5 to 13 years old. A total of 144 boys and girls were recruited from the kindergarten, elementary schools and middle schools in Seoul. With facial dimensions obtained, cluster analysis was performed to categorize them into similar facial groups. For each cluster, an optimal mask was designed and manufactured using a 3D printer. In addition, lung function data were obtained from 62 subjects and compared with those of normal adults. The pulmonary physiological results were subsequently used to suggest a test method for mask certification. Results: Facial shapes were classified into tree clusters: small, medium, and large. The face width and length for the first group were small with high nosal protrusion. The face width and length for the second group were the largest among the three clusters. The third group had the largest angle of nose root - gnathion(n-prn-gn). Age was the most significant variable in the facial dimensions. Children's pulmonary physiological capacity was about 60% of adults' capacity. The results of fit test using the prototype masks developed showed very good fits for children. Conclusions: For Korean children, three mask sizes will be sufficient and practical for providing protection against yellow dust and fine particulates. Anthropometric data obtained using digitalized 3D face analysis can be very effective for designing respiratory devices. 3D images can be accurate and easily measured for multiple dimensions, particularly for curved areas of the face. It is imperative to adopt different test methods for certifying respiratory protective devices for children, since their pulmonary physiological capacity is inferior compared with that of adults.

• Korean Journal of Microbiology
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• v.43 no.3
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• pp.201-209
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• 2007

The CFDA (6-carboxyfluorescein diacetate) direct viable count method and plate count (PC) method using conventional nutrient broth (NB) medium and $10^{-2}$ diluted NB (DNB) medium were applied to samples collected from Mt. Yongdoo In Andong, in an effect to determine the number of living bacteria pine mushroom forest soil. The number of living bacteria determined via plate count in NB medium comprised $5{\sim}8%$ of the CFDA direct viable count, and the bacteria in the DNB medium comprised $40{\sim}47%$. This result indicated that viable but nonculturable (VBNC) bacteria existed in the pine mushroom forest soil at a high percentage. The phylogenetic characteristics of the VBNC bacterial populations in the samples of pine mushroom (Tricholoma matsutake) forest soil were analyzed via the direct extraction of DNA and 16S rDNA-ARDRA. The 115 clones from pine mushroom forest soil were clustered into 31 different RFLP phylotypes by ARDRA. Based on the 16S rDNA sequences, the 31 ARDRA clusters were classified into 6 phylogenetic groups: ${\alpha}-,\;{\beta}-,\;{\gamma}-Proteobacteria$, Acidobacteria, Actinobacteria and Firmicutes. Among these bacterial populations, approximately 85% were classified as members of phylum Acidobacteria. The Acidobacteria phylum was shown to exist abundantly in the pine mushroom forest soil.

• The Korean Journal of Mycology
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• v.25 no.3 s.82
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• pp.176-190
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• 1997

Sixty-three isolates of Lentinus edodes obtained from Korea were used to assess the genetic similarity by isozyme polymorphisms and random amplified polymorphic DNA patterns. The activities of esterase, peroxidase and acid phosphatase displayed 10, 7 and 3 distinct isozyme patterns, respectively. By combining the isozyme patterns obtained with the 3 enzymes, every isolate showed its own distinct electrophoretic phenotypes. A distance matrix calculated between all pairs of 63 electrophoretic phenotypes based on the presence or abscence of isozyme bands were analyzed by the group-average method. Results of the cluster analysis assinged the 63 phenotypes into six major groups. In the analysis of random amplified polymorphic DNA patterns, all isolates of Lentinus edodes were devided into five RAPD groups.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1809-1815
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• 2008

This experiment simulated the fire driven flow of an underground station through parallel processing method. Fire analysis program FDS(Fire Dynamics Simulation), using LES(Large Eddy Simulation), has been used and a 6-node parallel cluster, each node with 3.0Ghz_2set installed, has been used for parallel computation. Simulation model was based on the Kwangju-geumnan subway station. Underground station, and the total time for simulation was set at 600s. First, the whole underground passage was divided to 1-Mesh and 8-Mesh in order to compare the parallel computation of a single CPU and Multi-CPU. With matrix numbers($15{\times}10^6$) more than what a single CPU can handle, fire driven flow from the center of the platform and the subway itself was analyzed. As a result, there seemed to be almost no difference between the single CPU's result and the Multi-CPU's ones. $3{\times}10^6$ grid point one employed to test the computing time with 2CPU and 7CPU computation were computable two times and fire times faster than 1CPU respectively. In this study it was confirmed that CPU could be overcome by using parallel computation.